AIMC Topic: Retrospective Studies

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Robot-Assisted Transarterial Chemoembolization of Hepatocellular Carcinoma Using a Coaxial Microcatheter Driving Controller-Responder Robot System: Clinical Pilot Study.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To evaluate the feasibility and safety of robot-assisted transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) using a new coaxial microcatheter driving controller-responder robot (CRR) system.

The Feasibility, Proficiency, and Mastery Learning Curves in 635 Robotic Pancreatoduodenectomies Following a Multicenter Training Program: "Standing on the Shoulders of Giants".

Annals of surgery
OBJECTIVE: To assess the feasibility, proficiency, and mastery learning curves for robotic pancreatoduodenectomy (RPD) in "second-generation" RPD centers following a multicenter training program adhering to the IDEAL framework.

Automatic Detection of Pancreatic Lesions and Main Pancreatic Duct Dilatation on Portal Venous CT Scans Using Deep Learning.

Investigative radiology
OBJECTIVES: This study proposes and evaluates a deep learning method to detect pancreatic neoplasms and to identify main pancreatic duct (MPD) dilatation on portal venous computed tomography scans.

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

Pharmacoepidemiology and drug safety
PURPOSE: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to eva...

Crowd-Sourced Deep Learning for Intracranial Hemorrhage Identification: Wisdom of Crowds or Laissez-Faire.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Researchers and clinical radiology practices are increasingly faced with the task of selecting the most accurate artificial intelligence tools from an ever-expanding range. In this study, we sought to test the utility of ensem...

Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features.

Scientific reports
To investigate whether the combination scheme of deep learning score (DL-score) and radiomics can improve preoperative diagnosis in the presence of micropapillary/solid (MPP/SOL) patterns in lung adenocarcinoma (ADC). A retrospective cohort of 514 co...

CoAt-Mixer: Self-attention deep learning framework for left ventricular hypertrophy using electrocardiography.

PloS one
Left ventricular hypertrophy is a significant independent risk factor for all-cause mortality and morbidity, and an accurate diagnosis at an early stage of heart change is clinically significant. Electrocardiography is the most convenient, economical...